Principles of Data Science

Livro digital

Título:
Principles of Data Science

Autor:
Shaun V. Ault, Soohyun Nam Liao, Larry Musolino

Categoria:
Tecnologia > Dados

Doador:
Raffaello D. N.

Sinopse:
Data science is presented as a complete practice, from collecting evidence to communicating a responsible conclusion. The OpenStax authors organize the material into four units covering data collection, statistical analysis, prediction and modeling, and professional ethics. Chapters move from datasets, web scraping, cleaning, and Python foundations through probability, regression, forecasting, machine learning, neural networks, visualization, validation, and executive reporting. The breadth is matched by a deliberately instructional structure. Worked examples, Python applications, key terms, quantitative problems, critical-thinking questions, and group projects make each topic usable in a classroom or for independent study. Dedicated chapters on ethics throughout the data-science cycle and on reporting results prevent modeling from being separated from consent, bias, interpretation, and the obligations that accompany consequential decisions. Designed for readers without extensive coding or statistical experience, this substantial textbook supplies both a first course and a dependable reference. Appendices review Excel, RStudio, Python algorithms, and Python functions, while the main chapters build enough statistical and computational fluency to support later specialization. Readers leave with a connected view of how data is acquired, analyzed, modeled, challenged, visualized, and finally turned into action.